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The Art of Computer Game Design
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by summing the quotients of enemy units strengths divided by their ranges; thus, large close units are very dangerous and small distant units are only slightly dangerous. A similar calculation with friendly units yields a safety factor. By comparing the danger value at its position with the safety value at its position, a unit can decide whether it should exhibit bold behavior or timid behavior. Once this decision is made, the unit can look around it and measure the net danger minus safety in each position into which the unit could move. If it is feeling bold, it moves towards the danger; if it is feeling timid, it moves away. Thus, the use of fields allows a unit to assess a spatial array of factors. Another technique for coping with artificial smarts problems is so simple that it seems like cheating: change the game. If an element of the game is not tractable with artificial reckoning, remove it. If you can t come up with a good way to use a feature, you really have no choice but to delete it. For example, while designing TANKTICS, I encountered a problem with lakes. If a lake was concave in shape, the computer would drive its tanks to the shore, back up, and return to the shore. The concave lake created a trap for my artificial smarts algorithm. I wasted a great deal of time working on a smarter artificial smarts routine that would not be trapped by concave lakes while retaining desirable economies of motion. After much wasted effort I discovered the better solution: delete concave lakes from the map. Ideally, the experienced game designer has enough intuitive feel for algorithms that she can sense game factors that are intractable and avoid them during the design stages of the game. Most of us must discover these things the hard way and retrace our steps to modify the design. Experiencing these disasters is part of what provides the intuition. A special problem is the coordination of moves of many different units under the control of the computer. How is the computer to assure that the different units move in a coordinated way and that traffic jams don t develop One way is to use a sequential planning system coupled with a simple test for the position of other units. Thus, unit #1 moves first, then #2, then #3, with each one avoiding collisions. I can assure you from my own experience that this system replaces collisions with the most frustrating traffic jams. A better way uses a virtual move system in which each unit plans a virtual move on the basis of the virtual positions of all units. Here s how it works: we begin with an array of real positions of all computer units. We create an array of virtual positions and initialize all virtual values to the real values. Then each unit plans its move, avoiding collisions with the virtual positions. When its move is planned, it places its planned final position into the virtual array. Other units then plan their moves. After all units have planned one virtual move, the process repeats, with each unit planning its move on the basis of the interim virtual move array. This huge outer loop should be convergent; after a sufficient number of iterations the routine terminates and the virtual positions form the basis of the moves made by the computer s units. This technique should be useful for coordinating the moves of many units and preventing traffic jams. No matter how good an algorithm is, it has a limited regime of applicability. The odds are that a specific algorithm will work best under a narrow range of conditions. A good game design must
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